1. Field of the Invention
The present invention relates to a low-complexity and low-power-consumption turbo decoder with a variable scaling factor, and more particularly, to a low-complexity and low-power-consumption turbo decoder in which performance of the turbo decoder is enhanced by applying a variable scaling factor producing optimal performance in each decoding convergence area using a sign difference ratio (SDR) and limiting an iterative-decoding number, and power consumption is reduced by reducing the average number of decoding iterations.
2. Discussion of Related Art
As mobile communications services including multimedia services such as video, wireless Internet, and the like are provided, low bit error rate (BER) performance as well as high-speed transmission are required. Research for error correction schemes and performance enhancement is being actively performed. At present, turbo codes have been adopted as error correction codes for next-generation mobile communications systems such as High Speed Downlink Packet Access (HSDPA), WiBro, and the like.
FIGS. 1A and 1B illustrate a conventional turbo decoder for decoding turbo codes. Referring to FIG. 1A, a conventional turbo decoder comprises two component decoders 110 and 130 in series. The component decoders 110 and 130 perform iterative decoding while exchanging extrinsic information generated. The component decoders 110 and 130 employ decoding algorithms, such as a Log-MAP (LMAP) algorithm, a Max-Log-MAP (MLMAP) algorithm, and the like.
The LMAP algorithm is a version of Maximum A Posteriori (MAP) algorithm that is implemented on a log domain, which is an optimal algorithm for decoding an information word on a trellis. The MLMAP algorithm is a version of the LMAP algorithm, however the MLMAP algorithm is more simply implemented than the LMAP algorithm through approximation in a metric operation process.
In particular, the MLMAP algorithm reduces complexity and decoding delay of probability-based iterative decoding and is easily implemented, unlike the LMAP algorithm. However, in case that the receiver can recognize an exact signal-to-noise ratio, the decoding performance of the MLMAP algorithm becomes worse, compared to that of the LMAP algorithm.
To address the performance degradation of the MLMAP algorithm, an Enhanced Max-Log-MAP (EMLMAP) algorithm has been suggested in which an output of each of the component decoders 110 and 130 is multiplied by a fixed scaling factor α for iterative decoding, as shown in FIG. 1B.
When an encoded block is relatively small, the decoding performance of the EMLMAP algorithm becomes substantially similar to that of the LMAP algorithm. However, when the encoded block is large, the decoding performance of the EMLMAP algorithm becomes worse, compared to that of the LMAP algorithm.
For a turbo decoder with the EMLMAP algorithm, as an iterative-decoding number increases, a bit error rate and a frame error rate decrease with gradually reduced enhancement. Therefore, after the turbo codes reach their performance limit, the iterative decoding process only incurs additional operation and decoding delay.
In the turbo decoder, a time point to stop iterative decoding with decoding performance unchanged determines power consumption and a decoding-induced time delay. There is a need for a simple means capable of limiting an iterative-decoding number using a simply set threshold value.